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HybridHR-Net:Action Recognition in Video Sequences Using Optimal Deep Learning Fusion Assisted Framework

computers, Materials & Continua 2023年第9期76卷 3275-3295页

作者： Muhammad Naeem Akbar Seemab Khan Muhammad Umar Farooq Majed Alhaisoni Usman Tariq Muhammad Usman Akram Department of Computer Engineering National University of Sciences and Technology(NUST)Islamabad46000Pakistan Department of Robotics SMME NUSTIslamabad45600Pakistan Computer Sciences Department College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh11671Saudi Arabia Management Information System Department College of Business AdministrationPrince Sattam bin Abdulaziz UniversityAl-Kharj16278Saudi Arabia

The combination of spatiotemporal videos and essential features can improve the performance of human action recognition(HAR);however,the individual type of features usually degrades the performance due to similar actions and complex *** deep convolutional neural network has improved performance in recent years for several computer vision applications due to its spatial *** article proposes a new framework called for video surveillance human action recognition dubbed *** a few selected datasets,deep transfer learning is used to pre-trained the EfficientNet-b0 deep learning *** optimization is employed for the tuning of hyperparameters of the fine-tuned deep *** of fully connected layer features,we considered the average pooling layer features and performed two feature selection techniques-an improved artificial bee colony and an entropy-based *** a serial nature technique,the features that were selected are combined into a single vector,and then the results are categorized by machine learning *** publically accessible datasets have been utilized for the experimental approach and obtained notable accuracy of 97%,98.7%,100%,99.7%,and 96.8%,***,a comparison of the proposed framework with contemporarymethods is done to demonstrate the increase in accuracy.

关键词： Action recognition entropy deep learning transfer learning artificial bee colony feature fusion

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Exploring the Relationships between Dynamic Capabilities, Digital Transformation, and IT-Business Alignment 12

Exploring the Relationships between Dynamic Capabilities, Di...

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12th International Conference on Cyber and IT Service Management, CITSM 2024

作者： Kosasi, Sandy Sukmana, Husni Teja Yuliani, I Dewa Ayu Eka Laipaka, Robertus Fitriani, Diana Madhiyono Information System Stmik Pontianak Pontianak West Kalimantan Indonesia Information Engineering Syarif Hidayatullah State Islamic University Jakarta Jakarta Indonesia Computer Science Stmik Pontianak Pontianak West Kalimantan Indonesia

ISBN: (纸本)9798331528799

Business and IT alignment is crucial to business organizations, navigating digital transformation, leveraging dynamic capabilities, facilitating smooth integration of digital technologies, and creating competitive added value in managing digital. Nevertheless, there is no literature discussing the influence of dynamic capabilities in doing business and IT alignment through digital transformation in managing digital business. The objective of the research is to explore and ensure the full impact of the digital transformation construction in bringing business and IT alignment together with every indicator of the effects of dynamic capacity with the availability and readiness to manage a digital business-convergence triangulation research method with explanatory design through follow-up explanation. The research population was taken from all the digital businesses that had run them for at least five years. 198 of the 238 respondents completed the questionnaire online through Google Forms using a random sampling technique with a response rate of 83.19%. The Likert scale is used to process and analyze data using the SEM-PLS method. The results of the research showed it turns out that the assumption of managing digital business is very resistant to the need to harmonize business and IT from the influence of digital transformation is not proven at all, and the existence of the linkage of dynamic capabilities in carrying out the alignment of business and IT. © 2024 IEEE.

关键词： digital businesses digital transformation dynamic capabilities IT-business alignment

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Improved Bat Algorithm with Deep Learning-Based Biomedical ECG Signal Classification Model

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computers, Materials & Continua 2023年第2期74卷 3151-3166页

作者： Marwa Obayya Nadhem NEMRI Lubna A.Alharbi Mohamed K.Nour Mrim M.Alnfiai Mohammed Abdullah Al-Hagery Nermin M.Salem Mesfer Al Duhayyim Department of Biomedical Engineering College of EngineeringPrincess Nourah Bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Information Systems College of Science and Art at MahayilKing Khalid UniversitySaudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversitySaudi Arabia Department of Computer Sciences College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Computer Science College of ComputerQassim UniversitySaudi Arabia Department of Electrical Engineering Faculty of Engineering and TechnologyFuture University in EgyptNew Cairo11835Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam Bin Abdulaziz UniversitySaudi Arabia

With new developments experienced in Internet of Things(IoT),wearable,and sensing technology,the value of healthcare services has *** evolution has brought significant changes from conventional medicine-based healthcare to real-time observation-based *** Electrocardiogram(ECG)signals are generally utilized in examination and diagnosis of Cardiovascular Diseases(CVDs)since it is quick and non-invasive in *** to increasing number of patients in recent years,the classifier efficiency gets reduced due to high variances observed in ECG signal patterns obtained from *** such scenario computer-assisted automated diagnostic tools are important for classification of ECG *** current study devises an Improved Bat Algorithm with Deep Learning Based Biomedical ECGSignal Classification(IBADL-BECGC)*** accomplish this,the proposed IBADL-BECGC model initially pre-processes the input ***,IBADL-BECGC model applies NasNet model to derive the features from test ECG *** addition,Improved Bat Algorithm(IBA)is employed to optimally fine-tune the hyperparameters related to NasNet ***,Extreme Learning Machine(ELM)classification algorithm is executed to perform ECG classification *** presented IBADL-BECGC model was experimentally validated utilizing benchmark *** comparison study outcomes established the improved performance of IBADL-BECGC model over other existing methodologies since the former achieved a maximum accuracy of 97.49%.

关键词： Data science ECG signals improved bat algorithm deep learning biomedical data data classification machine learning

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Deep Learning Enabled Intelligent Healthcare Management system in Smart Cities Environment

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computers, Materials & Continua 2023年第2期74卷 4483-4500页

作者： Hanan Abdullah Mengash Lubna A.Alharbi Saud S.Alotaibi Sarab AlMuhaideb Nadhem Nemri Mrim M.Alnfiai Radwa Marzouk Ahmed S.Salama Mesfer Al Duhayyim Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department of Computer Science College of Computers and Information TechnologyTabuk UniversityTabuk71491Saudi Arabia Department of Information Systems College of Computing and Information SystemUmm Al-Qura UniversitySaudi Arabia Department of Computer Science College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Information Systems College of Science and Arts at MuhayelKing Khalid UniversitySaudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.Box 11099Taif21944Saudi Arabia Department of Electrical Engineering Faculty of Engineering&TechnologyFuture University in EgyptNew Cairo11845Egypt Department of Computer Science College of Sciences and Humanities-AflajPrince Sattam bin Abdulaziz UniversitySaudi Arabia

In recent times,cities are getting smart and can be managed effectively through diverse architectures and *** cities have the ability to support smart medical systems that can infiltrate distinct events(i.e.,smart hospitals,smart homes,and community health centres)and scenarios(e.g.,rehabilitation,abnormal behavior monitoring,clinical decision-making,disease prevention and diagnosis postmarking surveillance and prescription recommendation).The integration of Artificial Intelligence(AI)with recent technologies,for instance medical screening gadgets,are significant enough to deliver maximum performance and improved management services to handle chronic *** latest developments in digital data collection,AI techniques can be employed for clinical decision making *** the other hand,Cardiovascular Disease(CVD)is one of the major illnesses that increase the mortality rate across the ***,wearables can be employed in healthcare systems that instigate the development of CVD detection and *** this motivation,the current study develops an Artificial Intelligence Enabled Decision Support system for CVD Disease Detection and Classification in e-healthcare environment,abbreviated as AIDSS-CDDC *** proposed AIDSS-CDDC model enables the Internet of Things(IoT)devices for healthcare data ***,the collected data is saved in cloud server for *** by,training 4484 CMC,2023,vol.74,no.2 and testing processes are executed to determine the patient’s health *** accomplish this,the presented AIDSS-CDDC model employs data preprocessing and Improved Sine Cosine Optimization based Feature Selection(ISCO-FS)*** addition,Adam optimizer with Autoencoder Gated RecurrentUnit(AE-GRU)model is employed for detection and classification of *** experimental results highlight that the proposed AIDSS-CDDC model is a promising performer compared to other existing models.

关键词： Smart cities e-healthcare decision support system cardiovascular disease deep learning feature selection

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Taxonomy of Multi-Agent systems Attacks and their Defense Tactics in Certifying Security of Cyber Physical systems

Taxonomy of Multi-Agent Systems Attacks and their Defense Ta...

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2023 International Conference on Advances in Computation, Communication and information Technology, ICAICCIT 2023

作者： Jain, Garima Solomon Jebaraj, N.R. Noida Institute of Engineering and Technology Department of Computer Science & Business System Uttar Pradesh Greater Noida India Department of Computer Science and Information Technology Bangalore India

ISBN: (纸本)9798350344387

The utilization of multi-agent systems has been increasingly prevalent across various sectors, owing to their notable efficacy in execution. However, a multitude of hazards exist that possess the capability to undermine the integrity of the agent and pose a threat to the overall security of the system. Therefore, it is crucial to carefully evaluate and address security vulnerabilities during the process of creating Multi-Agent systems (MAS). This survey assesses different models that aim to guarantee the security of Multi-Agent systems (MAS). These models were developed based on principles related to the agents' functionality and communication. This study offers a comprehensive examination and categorization of the prevailing threats targeting Multi-Agent systems (MASs). Following this, we conduct a comprehensive analysis and assessment of diverse security strategies described in scholarly sources, classifying them into prevention, detection, and resiliency approaches based on their established credibility and reliability. In conclusion, we offer a suggestion for the optimal security approach to address particular types of threats, considering the most recent breakthroughs in the field of study. © 2023 IEEE.

关键词： Attacks Cyber Physical systems Multi Agent systems Resiliency Security

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Deep Learning Techniques for Advanced Large-Scale Data Processing 15

Deep Learning Techniques for Advanced Large-Scale Data Proce...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Sunil, M.P. Shekhawat, Jyoti Vanaja, T. Mohammed, Vazeer Ali Thaware, Shailesh J. Singh, Vaishali Karnataka Bangalore India Department of Computer Science & Application Vivekananda Global University Jaipur India Department of Information Technology Prince Shri Venkateshwara Padmavathy Engineering College Chennai127 India Department of Computer & Information System Lewis University Illinois United States Department of Computer Engineering Vishwakarma Institute of Technology Pune India Maharishi School of Engineering and Technology Maharishi University of Information Technology Uttar Pradesh India

ISBN: (纸本)9798350370249

Deep getting to know techniques have become increasingly more popular due to their potential to improve huge-scale records processing performance. Leveraging specialized hardware which includes GPUs, deep getting to know algorithms can attain mind-blowing pace will increase compared to traditional algorithms. further, deep gaining knowledge of fashions can discover complicated non-linear relationships in big datasets, permitting greater accurate overall performance and less fake predictions. Latest advances in deep mastering have enabled it to be implemented to remedy a plethora of information processing duties, from photo recognition to natural language processing. CNNs, RNNs, and GANs are a number of the maximum famous deep gaining knowledge of fashions used in tackling complex data processing obligations. agencies consisting of Google, fb, and Amazon use these sophisticated frameworks to build predictive models that help improve numerous programs. Deep getting to know strategies offer exquisite ability to take massive-scale information processing to the following stage. corporations are increasingly more becoming privy to the emerging opportunities, and actively investing in deep mastering to liberate the untapped strength of their information. ©2024 IEEE.

关键词： Large datasets

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BAV-DSS: Blockchain Assisted Verifiable Data Sharing Scheme with Fast Encryption and Outsourced Decryption for IoT 24th

BAV-DSS: Blockchain Assisted Verifiable Data Sharing Scheme ...

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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Huang, Yao Yu, Zhongyuan Wang, Guijuan Chai, Baobao Zhang, Hongliang Jinan250353 China Shandong Provincial Key Laboratory of Industrial Network and Information System Security Shandong Fundamental Research Center for Computer Science Jinan250353 China School of Information Science and Engineering Lanzhou University Lanzhou730000 China School of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9789819615414

Many sophisticated cloud platforms are available to provide services such as storage and computation for Internet of Things (IoT) applications. However, with the concerns about the semi-trusted nature of cloud platforms, data security and privacy have been gaining broad attention. In this paper, we propose a blockchain-assisted verifiable data sharing scheme (BAV-DSS) for IoT. The BAV-DSS features fine-grained access control, fast encryption, and outsourced decryption with verifiability. Specifically, with the application of ciphertext-policy attribute-based encryption (CP-ABE), flexible access control is enabled. Blockchain is employed to store public keys, generate account addresses, and perform data verification. Furthermore, the selective replayable chosen ciphertext attacks (sRCCA) security of BAV-DSS is proved, and the simulation results indicate that BAV-DSS obtains high efficiency and practicality compared to other schemes. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Cloud platforms

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Chatbots: Understanding Their World, Classification, and Their Current State 2nd

Chatbots: Understanding Their World, Classification, and The...

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Emergent Converging Technologies and Biomedical systems Select Proceedings of the 2nd International Conference, ETBS 2022

作者： Singh, Amit Sharma, K.K. Kumar, Parveen Vats, Sandeep Kumar Computer Science and Engineering Department Sanskriti University Mathura UP Chatta India Centre for Railways Information System Chanakyapuri Delhi India

ISBN: (纸本)9789819922703

An extraordinary growth is being witnessed for mobile devices and their ever-growing computational powers. Also, the chip demand is very high. This demand is not only coming from the software industry, but almost all the other sectors also contribute to this enormous growth. With the recent innovations in chip manufacturing, complemented with very high demands, compute power costs are getting reduced at a significant rate. The computation power of chips fuels the artificial intelligence (AI) technologies to harness them. AI is a very computation resource demanding technology, and, in many cases, it requires specialized computational resources. Due to deep mobile penetration in the society, AI technologies such as Data Science and NLP are taking great pace. On the other hand, chatbots are gaining momentum beyond customer care and typical use cases. This paper analyzes the history, growth, and new trends of chatbots. Especially the impact of AI on bot technologies and the road ahead. This paper will take a look at the chatbot journey. It also examines where chatbots are making an impact on human lives. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Natural language processing systems

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Sentiment Analysis of Public Opinion on Twitter about the Implementation of the Merdeka Curriculum Using the Support Vector Machine Algorithm

Sentiment Analysis of Public Opinion on Twitter about the Im...

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2023 International Conference on Modeling and E-information Research, Artificial Learning and Digital Applications, ICMERALDA 2023

作者： Ramadhanti, Intan Widodo Nugraheni, Murien Universitas Negeri Jakarta Informatics and Computer Engineering Education Jakarta Indonesia Universitas Negeri Jakarta Information System and Technology Jakarta Indonesia

ISBN: (纸本)9798350369359

In 2022 the Head of Standards, Curriculum, Education Assessment (BSKAP) No. 0441HIKR/2022 issued a Decree (SK) regarding Education Units for the Implementation of the Merdeka Curriculum in 140 thousand educational units in Indonesia. The implementation of this new curriculum raises various public opinions on social media Twitter. Therefore, research on the analysis of public sentiment on the implementation of the Merdeka Curriculum was carried out. The tweets taken are tweets with positive and negative sentiments. This study aims to see whether the SVM algorithm is good at carrying out text classification for sentiment analysis of the Merdeka Curriculum by looking at the accuracy value and describing how the public's sentiment on Twitter is about the Merdeka Curriculum. The data used is a dataset of 1,186 tweets, that is 363 positive tweets and 823 negative tweets. The results showed that the accuracy of the Support Vector Machine algorithm with linear, polynomial, and sigmoid kernels was 91.82% and the RBF kernel was 89.88%. As well as seen from the results of the sentiment analysis of implementing the Merdeka Curriculum there were more negative responses, one of which was regarding too many assignments and projects that made students feel tired and stressed. © 2023 IEEE.

关键词： Support vector machines

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An Improved Method for Approximating the Infinite-Horizon Value Function of the Discrete-Time Switched LQR Problem

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Journal of systems Science & Complexity 2024年第1期37卷 22-39页

作者： HOU Tan LI Yuanlong LIN Zongli Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China Charles L.Brown Department of Electrical and Computer Engineering University of VirginiaCharlottesvilleVA 22904-4743USA

This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR *** particular,the authors propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value *** method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration,and thus,the proposed approach is capable of achieving a better approximation for a given computation time compared with the existing *** numerical examples are presented in this paper to illustrate the effectiveness of the proposed method.

关键词： Optimal control switched linear systems switched LQR problem.

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